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Swarm Intelligence and Bio-Inspired Computation

- Theory and Applications

Forfatter: info mangler
Bog
  • Format
  • Bog, hardback
  • Engelsk

Beskrivelse

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers.

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  • Vægt770 g
  • coffee cup img
    10 cm
    book img
    15,2 cm
    22,9 cm

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    Classification Data mining Genetic algorithms Ontology. Scheduling Traveling-salesman problem Swarm intelligence Protein folding Semantic Web Structural optimization Intensification OPTIMIZATION Hidden Markov models Metaheuristics Pattern classification Ant algorithm Modeling and Simulation Monte-Carlo-Simulation Port operations Diversification Peer to Peer Convergence analysis Neuro-Fuzzy System Metaheuristic algorithms Clustering Gradient Cuckoo Search Algorithm Harmony Search Algorithm Global, optimization Cuckoo Search Memetic Algorithms Particle swarm optimization Firefly Algorithm Artificial neural network Bio-inspired Local search Resilient Supply Chain Virtual enterprise Scheduling problem Feature selection: Generic Algorithm Self-adaptation Ant colony algorithm Bat Algorithm Intelligent Algorithms Problem-oriented Multimodal Separable Metaheuristic algorithm Ant colony's labor division Artificial bee colony algorithm Artificial neural network training Artificial plant optimization algorithm Automatic music composition Apical dominance phenomenon Bee Algorithm Biologically inspired metaheuristic algorithms Dynamic berth allocation Edge-based movement Firefly algorithms Container transportation Fuzzy user profile Graph 3-coloring problem Glowworm algorithm Dynamic trajectory Interactive music composition Levy Flights Inventory management system Modeling-to-generate-alternatives Nonseparable Optimum-path forest classifier Particle swam optimizer Intelligent music composition Photosynthesis phenomenon Supervised music composition Test functions Krill Herd Unsupervised music composition Phototropism phenomenon Pull production system unimodal Web content filtering
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